English

Deterministic Truncation of Linear Matroids

Data Structures and Algorithms 2014-04-18 v1 Discrete Mathematics

Abstract

Let M=(E,I)M=(E,{\cal I}) be a matroid. A {\em kk-truncation} of MM is a matroid {M=(E,I)M'=(E,{\cal I}')} such that for any AEA\subseteq E, AIA\in {\cal I}' if and only if Ak|A|\leq k and AIA\in {\cal I}. Given a linear representation of MM we consider the problem of finding a linear representation of the kk-truncation of this matroid. This problem can be abstracted out to the following problem on matrices. Let MM be a n×mn\times m matrix over a field F\mathbb{F}. A {\em rank kk-truncation} of the matrix MM is a k×mk\times m matrix MkM_k (over F\mathbb{F} or a related field) such that for every subset I{1,,m}I\subseteq \{1,\ldots,m\} of size at most kk, the set of columns corresponding to II in MM has rank I|I| if and only of the corresponding set of columns in MkM_k has rank I|I|. Finding rank kk-truncation of matrices is a common way to obtain a linear representation of kk-truncation of linear matroids, which has many algorithmic applications. A common way to compute a rank kk-truncation of a n×mn \times m matrix is to multiply the matrix with a random k×nk\times n matrix (with the entries from a field of an appropriate size), yielding a simple randomized algorithm. So a natural question is whether it possible to obtain a rank kk-truncations of a matrix, {\em deterministically}. In this paper we settle this question for matrices over any finite field or the field of rationals (Q\mathbb Q). We show that given a matrix MM over a field F\mathbb{F} we can compute a kk-truncation MkM_k over the ring F[X]\mathbb{F}[X] in deterministic polynomial time.

Keywords

Cite

@article{arxiv.1404.4506,
  title  = {Deterministic Truncation of Linear Matroids},
  author = {Daniel Lokshtanov and Pranabendu Misra and Fahad Panolan and Saket Saurabh},
  journal= {arXiv preprint arXiv:1404.4506},
  year   = {2014}
}

Comments

23 pages

R2 v1 2026-06-22T03:52:58.313Z